2023

Johnson, L. K., Mahoney, M. J., Desrochers, M. L., and Beier, C. M. Mapping historical forest biomass for stock-change assessments at parcel to landscape scales. Forest Ecology and Management, 546, 121348. https://doi.org/10.1016/j.foreco.2023.121348

Mahoney, M. J., Johnson, L. K., Silge, J., Frick, H., Kuhn, M., and Beier, C. M. Assessing the performance of spatial cross-validation approaches for models of spatially structured data. In review. https://doi.org/10.48550/arXiv.2303.07334

Mahoney, M. J., Johnson, L. K., and Beier C. M. 2023. AI for shrubland identification and mapping. In Sun Z, Cristea N, Rivas P (eds.), Artificial Intelligence in Earth Science, 295-316. Elsevier. ISBN 978-0-323-91737-7. https://doi.org/10.1016/B978-0-323-91737-7.00010-4

2022

Mahoney, M. J., Johnson, L. K., Guinan, A. Z., and Beier, C. M. (2022). Classification and mapping of low-statured shrubland cover types in post-agricultural landscapes of the US Northeast. International Journal of Remote Sensing 43:19-24 7117-7138. https://doi.org/10.1080/01431161.2022.2155086.

Johnson, L. K., Mahoney, M. J., Bevilacqua, E., Stehman, S. V., Domke, G. M., & Beier, C. M. (2022). Fine-resolution landscape-scale biomass mapping using a spatiotemporal patchwork of LiDAR coverages. International Journal of Applied Earth Observation and Geoinformation 114 103059. https://doi.org/10.1016/j.jag.2022.103059.

Mahoney, M. J., Johnson, L. K., Bevilacqua, E., and Beier, C. M. (2022). Ground noise filtering produces inferior models of forest aboveground biomass. GIScience and Remote Sensing 59:1 1266-1280. https://doi.org/10.1080/15481603.2022.2103069

Desrochers, M. L., Tripp, W., Logan, S., Bevilacqua, E., Johnson, L., & Beier, C. M. (2022). Ground-Truthing Forest Change Detection Algorithms in Working Forests of the US Northeast. Journal of Forestry fvab075. https://doi.org/10.1093/jofore/fvab075